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VERSION:2.0
PRODID:-//AMSE//Event Calendar//FR
CALSCALE:GREGORIAN
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BEGIN:VEVENT
UID:event-8332@www.amse-aixmarseille.fr
DTSTAMP:20260430T011643Z
CREATED:20260430T011643Z
LAST-MODIFIED:20260430T011643Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:phd seminar - Rosnel Sessinou
DTSTART:20210921T090000Z
DTEND:20210921T094500Z
DESCRIPTION:The least square estimator can be shown to depend only on a sin
 gle parameter\, the precision matrix. We show that a regularized estimate o
 f the precision matrix can be directly used to obtain the least square solu
 tion even when the number of covariates can be strictly larger than the sam
 ple size. As biases can occur from different choices of the precision matri
 x estimate\, we show how to construct a (nearly) unbiased estimator irrespe
 ctively of the sparsity within the data generating process. We call this es
 timator the Precision Least Squares (PrLS). Assuming stationarity for the c
 ovariates and the error process we show that the PrLS estimator is (i) asym
 ptotically Gaussian\, (ii) automatically free of the usual regularization b
 ias. As an application\, we employ the Precision Least Squares to estimate 
 the predictive connectedness among daily asset returns of 88 global banks. 
 We show that financial crisis corresponds to a collapse of financial linkag
 e in line with two financial theory predictions.\\n\\nContact: Kenza Elass 
 : kenza.elass[at]univ-amu.frCamille Hainnaux : camille.hainnaux[at]univ-amu
 .frDaniela Horta Saenz : daniela.horta-saenz[at]univ-amu.frJade Ponsard : j
 ade.ponsard[at]univ-amu.fr\n\nPlus d'informations: https://www.amse-aixmars
 eille.fr/fr/evenements/rosnel-sessinou-1
LOCATION:MEGA - Salle Carine Nourry\, 424\, Chemin du Viaduc\, 13080 Aix-en
 -Provence
URL;VALUE=URI:https://www.amse-aixmarseille.fr/fr/evenements/rosnel-sessinou-1
CONTACT:Kenza Elass : kenza.elass[at]univ-amu.frCamille Hainnaux : camille.
 hainnaux[at]univ-amu.frDaniela Horta Saenz : daniela.horta-saenz[at]univ-am
 u.frJade Ponsard : jade.ponsard[at]univ-amu.fr
TRANSP:OPAQUE
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